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DBMS > Atos Standard Common Repository vs. Kyligence Enterprise vs. Spark SQL vs. Transbase

System Properties Comparison Atos Standard Common Repository vs. Kyligence Enterprise vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA distributed analytics engine for big data, built on top of Apache KylinSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.39
Rank#276  Overall
#125  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorykyligence.io/­kyligence-enterprisespark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperAtos Convergence CreatorsKyligence, Inc.Apache Software FoundationTransaction Software GmbH
Initial release2016201620141987
Current release17033.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScalaC and C++
Server operating systemsLinuxLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesyesyes
Typing infopredefined data types such as float or dateoptionalyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoANSI SQL for queries (using Apache Calcite)SQL-like DML and DDL statementsyes
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesAll languages with LDAP bindingsJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonoyes
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlLDAP bind authenticationnofine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryKyligence EnterpriseSpark SQLTransbase
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